code: def forward(self, x):
      base_out = self.base(x)
      global_feat = self.gap(base_out)
      global_feat = self.flatten(global_feat)
      global_feat = self.bn(global_feat)
      return global_feat
  
file_path: PaddleDetection/ppdet/modeling/reid/resnet_embedding.py
imports: import os
  import paddle
  import paddle.nn.functional
  from paddle import nn
  from .resnet import ResNet50, ResNet101
  from ppdet.core.workspace import register
label_desc: Use image node_id 2 for calling the ResNetEmbedding obj's underlying member method code with example usage: obj.forward(x) and returns: global_feat